Architectural Innovation: Gradient Descent Stability Trumps Function Class
kalomaze · x · 2026-07-30
Continuing the discussion on model architecture design, researcher kalomaze added a crucial perspective. He argued that a critical factor in evaluating a new architecture (like linear attention) is whether "gradient descent has to do not-pathological things given the architectural shape."
He emphasized that this is a fundamentally different question from whether "the function class itself isn't necessarily buying you anything useful." It implies that even if an architecture theoretically offers better expressivity, the innovation is meaningless if the training process cannot optimize it effectively.
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